AI UX toolbox
Practical tools, frameworks, and guides to help you lead AI UX transformation
This toolbox is designed for UX leaders, researchers, and cross-functional teams navigating the shift from traditional UX to AI-integrated systems. Whether you're assessing your team's readiness, adapting your research methods, or building flexible, trustworthy AI experiences—this is where theory meets action.
Explore diagnostic assessments, research protocols, design templates, and collaboration models—all grounded in the Four Shifts of AI UX. Each tool is paired with articles that provide strategic context and real-world guidance to help you make AI UX work in practice.
This is a living toolkit, built with and for the community—your feedback, use cases, and insights will shape what comes next.
Founder
Marianne van Ooij
I’m an AI strategist with a background in organizational transformation, systems thinking, and design. I help teams move from AI experimentation to confident, responsible implementation—aligning intelligent technologies with real workflows, cultural dynamics, and strategic goals.
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My work spans AI adoption strategy, workflow redesign, and capability-building. I specialize in diagnosing readiness, mapping where AI fits (and where it doesn’t), and guiding change in a way that builds trust, momentum, and long-term value.
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AI UX Navigator was created to support that journey—offering grounded tools, methods, and case studies for teams navigating the shift to AI. The initiative reflects my broader focus: helping organizations not just use AI, but design better systems around it.
Contribute to the playbook
We welcome contributions from practitioners with deep expertise, lessons learned, or practical approaches to share. If you’re working on something aligned with these themes, we’d love to include your perspective as this playbook grows.
Interested in contributing?
Laying the groundwork & proving value through POCs
Laying the groundwork & proving value through POCs
Infrastructure & platform enablement
Insight-driven transformation in enterprise data & tooling workflows
DATA PLATFORMS | SYSTEM INTEGRATION
Summary: Modernized data and tooling workflows to support advanced analytics and automation.
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Focus areas: Data Transformation · Cloud Migration · Platform Design
Our services
CAPABILITIES
AI readiness assessment
Identify literacy gaps, trust barriers, workflow patterns, and capability levels through interviews and maturity mapping.
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AI opportunity portfolio and prioritization
Identify high-impact use cases, evaluate feasibility and ROI, and build a prioritized roadmap that sequences pilots toward scale.
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Adoption strategy and capability building
Design targeted training and enablement programs based on organizational maturity and real workflow needs.
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Workflow integration and pilot design
Map where AI delivers value, run targeted pilots, and build lightweight agents and GPTs aligned with day-to-day tasks.
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Behavioral tracking and measurement
Define adoption KPIs, measure sustained usage, and track cross-functional impact over time.
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Recent example: Confidential Financial Association (2025)
100 employees across five departments moved from 23 percent to 67 percent regular AI use in 16 weeks.
APPROACH
Start with diagnosis
Interview leaders and teams, map readiness and workflows, and identify high-value opportunities before recommending solutions.
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Design for readiness levels
Tailor interventions to different maturity groups to maximize impact and avoid one-size-fits-all programs.
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Build literacy foundations
Establish core skills and mental models that improve accuracy, speed, and decision quality across functions.
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Enable peer champions
Use peer-led examples and shared prompts to accelerate adoption with higher retention and lower change-management cost.
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Integrate into real workflows
Embed AI where it drives measurable efficiency and quality gains instead of requiring teams to change behavior to fit tools.
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Track behavior change over time
Measure usage patterns, capability growth, and workflow impact to ensure pilots translate into sustained ROI.
FOUNDATIONS & STRATEGIC FRAMEWORKS
→ Build shared language, vision, and readiness
AI UX maturity model: The five levels of AI UX
Assess where your organization stands in its AI UX journey and identify practical next steps. This model maps the progression from traditional UX to transformative AI experiences.
STRATEGY | FRAMEWORK
AI UX maturity assessment
Measure your team's current level of AI UX maturity. This tool helps identify strengths, gaps, and actionable steps across strategy, research, design, and collaboration.
MATURITY | ASSESSEMENT
ORGANIZATIONAL READINESS & LEADERSHIP
AI implementation that works: The organizational foundations of successful transformation
Discover the leadership, process, and team structures that enable AI to deliver tangible business outcomes. This article outlines the organizational foundations necessary for AI success.
LEADERSHIP | ALIGNMENT
Retooling vs. Retrofitting: Elevating UX from interface design to strategic partner
UX must evolve from a downstream function to a strategic partner in AI development. Learn how UX professionals can help organizations navigate AI's complexity and build user trust.
LEADERSHIP | ALIGNMENT
FOUNDATIONS & STRATEGIC FRAMEWORKS
→ Build shared language, vision, and readiness
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A pragmatic approach to AI
LEADERSHIP | AI UX STRATEGY
AI UX Maturity Mapping Template
Visualize your team’s progression across the five stages of AI UX maturity
TOOLKIT | CHECKLIST
The Four Shifts of AI UX: A framework for systemic design transformation
A comprehensive framework to implement AI UX
LEADERSHIP | AI UX STRATEGY
The AI UX Pitfall Checklist: Validating Experiences Before Launch
Practical tool for pre-launch evaluation of AI experiences
TOOLKIT | CHECKLIST
AI UX maturity model: The five levels of AI UX maturity
AI UX maturity model built on the 4 shifts
UX MATURITY | MATURITY ASSESSMENT
ORGANIZATION READINESS & LEADERSHIP
The UX Leader's 90-Day Plan for AI Transformation
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TOOLKIT | CHECKLIST
Cross-functional collaboration model
Ready-to-use templates, assessment tools, and methodologies
TOOLKIT | CHECKLIST
Building the AI UX playbook for your org
Organizational design for effective AI UX
TOOLKIT | CHECKLIST
DESIGNING & TESTING AI EXPERIENCES
From static to adaptive design
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TOOLKIT | CHECKLIST
Research Protocol Template for AI Systems
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UX RESEARCH | WORKFLOWS
AI UX Testing Checklist
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TOOLKIT | CHECKLIST
What's coming?
These tools and frameworks are currently in development. Each is designed to help you deepen your practice across the Four Shifts of AI UX.
By making these visible now, we invite feedback, collaboration, and curiosity as the toolbox grows.
Want early access or to shape these tools?
Let us know—your feedback directly informs how these resources evolve.
COMING SOON
Confidence Indicator UI examples
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Design reference patterns for communicating system uncertainty and AI confidence scores
LEADERSHIP | AI UX
Workshop Kit: The Four shifts in practice
Run an internal team session to activate thinking across strategy, design, research, and collaboration
LEADERSHIP | AI UX
Error state design patterns for probabilistic systems
Guidelines for designing adaptive error messages when AI gets it wrong—or isn’t sure
UX RESEARCH | WORKFLOWS
Shared metrics canvas (UX + ML)
Align performance goals across UX, product, and data science teams
LEADERSHIP | AI UX
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Get updates on new tools, frameworks, and articles—or contribute your own experience to help shape the field.